Search Results - (( java implementation based algorithm ) OR ( missing values machine algorithm ))
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Systematic review on missing data imputation techniques with machine learning algorithms for healthcare
Published 2022“…Many machine learning algorithms have been applied to impute missing data with plausible values. …”
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ExtraImpute: a novel machine learning method for missing data imputation
Published 2022“…This approach imputes each missing value that exists in features by predicting its value using other observed values in the dataset. …”
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
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Enhanced mechanism to handle missing data of Hadith classifier
Published 2011“…The correct branch to take is unknown if a feature tested is missing, and the algorithm must employed enhanced mechanisms to handle missing values. …”
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Proceeding Paper -
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Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…A common challenge is the occurrence of missing data during the data input process. Numerous studies have proposed methods to impute missing values for data across multiple fields. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…Today, with online marketing, banking, healthcare and other services, even the average householder is aware of encryption. The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…A common challenge is the occurrence of missing data during the data input process. Numerous studies have proposed methods to impute missing values for data across multiple fields. …”
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Imputation Analysis of Time-Series Data Using a Random Forest Algorithm
Published 2024“…To address the issue, this paper compared and evaluated four imputation methods: MissForest, MICE, Simplefill, and Softimpute which utilized Random Forest Algorithm. …”
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Conference or Workshop Item -
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Support Vector Machine Based Fault Diagnosis Of Power Transformer Using k Nearest Neighbor Imputed DGA Dataset
Published 2014“…Missing values are prevalent in real-world datasets and they may reduce predictive performance of a learning algorithm. …”
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Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid
Published 2022“…One of the major challenges when applying machine learning is to identify the best algorithm from a variety of algorithms to solve a problem. …”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…The main challenges of implementing ANPR algorithm on mobile phone are how to produce a higher coding efficiency, lower computational complexity, and higher scalability. …”
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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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An Apriori-based Data Analysis on Suspicious Network Event Recognition
Published 2019“…Then, each missing value in the test data set is decided by using the obtained rules. …”
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Conference or Workshop Item -
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Predicting uniaxial compressive strength using Support Vector Machine algorithm
Published 2019“…From the result, it was found that SVM is capable of predicting the missing values with a prediction trend accuracy of 75%. …”
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Café Web Based System Using Priority Scheduling Approach
Published 2017“…The priority scheduling algorithm is based on Control Processing Unit scheduling algorithm where it has a priority to execute tasks. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease
Published 2024“…The baseline LightGBM model with dropped missing values had an accuracy of 0.8333, sensitivity of 0.1081, precision of 0.3429, F1 score of 0.1644, and AUC of 0.6875. …”
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